code: def test_subgraph_large_index(device):
      subset = torch.tensor([50_000_000], device=device)
      edge_index = torch.tensor(
          [[50_000_000], [50_000_000]], device=device
      )
      edge_index, _ = subgraph(subset, edge_index, relabel_nodes=True)
      assert edge_index.tolist() == [[0], [0]]
  
file_path: pytorch_geometric/test/utils/test_subgraph.py
imports: import torch
  from torch_geometric.nn import GCNConv, Linear
  from torch_geometric.testing import withCUDA, withPackage
  from torch_geometric.utils import bipartite_subgraph, get_num_hops, index_to_mask, k_hop_subgraph, subgraph
label_desc: Use image node_id 3 for calling a global function with example usage: test_subgraph_large_index(device) without return types